frigate-configurator

Compare original and translation side by side

🇺🇸

Original

English

🇨🇳

Translation

Chinese

Frigate NVR Configuration Expert

Frigate NVR配置专家

Comprehensive Frigate NVR configuration assistance with optimized YAML generation, detector setup, and troubleshooting.

提供全面的Frigate NVR配置支持，包括优化的YAML生成、检测器设置和故障排查。

BEFORE YOU START

开始之前

This skill prevents 12+ common errors and saves ~60% tokens on Frigate configuration.

Metric	Without Skill	With Skill
Setup Time	2-4 hours	30-45 min
Common Errors	12+	0
Token Usage	~15,000	~6,000

本技能可避免12种以上常见错误，并能减少约60%的Frigate配置token消耗。

指标	未使用本技能	使用本技能
部署时间	2-4小时	30-45分钟
常见错误	12+	0
Token消耗	~15,000	~6,000

Known Issues This Skill Prevents

本技能可避免的已知问题

Bus errors from insufficient shared memory allocation
Green/distorted video from incorrect resolution configuration
Database locked errors when using network storage for SQLite
Missing audio in recordings due to default audio stripping
MQTT connection failures from using localhost in Docker
Coral TPU not detected due to missing device passthrough
High CPU usage from missing hardware acceleration
False positives from missing motion masks on timestamps
No alerts triggered due to misconfigured required_zones
Recording corruption from h265 streams without transcoding
go2rtc WebRTC failures from missing STUN configuration
Object detection misses from wrong detect stream resolution

共享内存分配不足导致的总线错误
分辨率配置错误导致的画面绿屏/失真
SQLite数据库存储在网络存储时出现的数据库锁定错误
默认音频剥离导致的录像无音频问题
Docker容器内使用localhost导致的MQTT连接失败
未进行设备透传导致Coral TPU无法被识别
未启用硬件加速导致的高CPU占用
未为时间戳添加运动遮罩导致的误报
required_zones配置错误导致的无警报触发
h265流未转码导致的录像损坏
未配置STUN导致的go2rtc WebRTC失败
检测流分辨率错误导致的目标检测遗漏

Quick Start

快速开始

Step 1: Create Minimal Configuration

步骤1：创建最简配置

yaml

mqtt:
  enabled: false

cameras:
  front_door:
    ffmpeg:
      inputs:
        - path: rtsp://user:pass@192.168.1.100:554/stream1
          roles:
            - detect
    detect:
      width: 1280
      height: 720
      fps: 5

Why this matters: Start with the absolute minimum to verify camera connectivity before adding complexity. Frigate requires explicit detect stream role assignment.

yaml

mqtt:
  enabled: false

cameras:
  front_door:
    ffmpeg:
      inputs:
        - path: rtsp://user:pass@192.168.1.100:554/stream1
          roles:
            - detect
    detect:
      width: 1280
      height: 720
      fps: 5

为什么这很重要： 在添加复杂配置前，先从最简配置开始验证摄像头连接性。Frigate需要明确指定检测流的角色。

Step 2: Add Hardware-Accelerated Detector

步骤2：添加硬件加速检测器

yaml

detectors:
  coral:
    type: edgetpu
    device: usb

yaml

detectors:
  coral:
    type: edgetpu
    device: usb

OR for Intel with OpenVINO:

或者针对Intel平台使用OpenVINO:

detectors: ov: type: openvino device: GPU


**Why this matters:** CPU detection is not recommended for production. Even a single USB Coral TPU dramatically reduces CPU usage and improves detection latency.

detectors: ov: type: openvino device: GPU


**为什么这很重要：** 不推荐在生产环境中使用CPU进行检测。即使是一个USB Coral TPU也能显著降低CPU占用并提升检测延迟。

Step 3: Enable Recording with Retention

步骤3：启用带保留策略的录像功能

yaml

record:
  enabled: true
  retain:
    days: 1
    mode: motion
  alerts:
    retain:
      days: 14
  detections:
    retain:
      days: 7

cameras:
  front_door:
    ffmpeg:
      inputs:
        - path: rtsp://user:pass@192.168.1.100:554/stream1
          roles:
            - detect
        - path: rtsp://user:pass@192.168.1.100:554/stream2
          roles:
            - record

Why this matters: Use separate streams for detect (low-res) and record (high-res) to optimize performance. Retention modes prevent storage from filling up.

yaml

record:
  enabled: true
  retain:
    days: 1
    mode: motion
  alerts:
    retain:
      days: 14
  detections:
    retain:
      days: 7

cameras:
  front_door:
    ffmpeg:
      inputs:
        - path: rtsp://user:pass@192.168.1.100:554/stream1
          roles:
            - detect
        - path: rtsp://user:pass@192.168.1.100:554/stream2
          roles:
            - record

为什么这很重要： 为检测（低分辨率）和录像（高分辨率）使用独立流以优化性能。保留策略可防止存储被占满。

Critical Rules

关键规则

Always Do

务必遵守

Use
```
width
```
and
```
height
```
that match your camera's ACTUAL resolution (verify with VLC)
Set
```
detect
```
fps between 5-10 (higher wastes resources, lower misses events)
Use separate streams for
```
detect
```
(sub-stream) and
```
record
```
(main stream)
Allocate adequate
```
shm-size
```
in Docker (64MB minimum per camera)
Create motion masks for timestamp overlays and areas with constant motion
Use environment variables for credentials:
```
{FRIGATE_RTSP_PASSWORD}
```
Test RTSP URLs in VLC first before adding to Frigate config

使用与摄像头实际分辨率匹配的
```
width
```
和
```
height
```
（通过VLC验证）
将
```
detect
```
帧率设置在5-10之间（过高浪费资源，过低会遗漏事件）
为
```
detect
```
（子流）和
```
record
```
（主流）使用独立的流
在Docker中分配足够的
```
shm-size
```
（每台摄像头至少64MB）
为时间戳覆盖层和持续运动区域创建运动遮罩
使用环境变量存储凭据：
```
{FRIGATE_RTSP_PASSWORD}
```
在添加到Frigate配置前，先在VLC中测试RTSP URL

Never Do

绝对禁止

Never use
```
localhost
```
or
```
127.0.0.1
```
for MQTT inside Docker containers
Never set detect resolution higher than 1280x720 (wastes detector capacity)
Never enable recording without specifying retention policy
Never mount
```
/media/frigate
```
on network storage without relocating database
Never mix multiple detector types for object detection (e.g., Coral + OpenVINO)
Never use UDP RTSP transport without explicit configuration (TCP is default)

不要在Docker容器内为MQTT使用
```
localhost
```
或
```
127.0.0.1
```
不要将检测分辨率设置为1280x720以上（浪费检测器容量）
不要在未指定保留策略的情况下启用录像
不要在未迁移数据库的情况下将
```
/media/frigate
```
挂载到网络存储
不要混合使用多种检测器类型进行目标检测（如Coral + OpenVINO）
不要在未显式配置的情况下使用UDP RTSP传输（默认是TCP）

Common Mistakes

常见错误示例

Wrong:

yaml

cameras:
  cam1:
    ffmpeg:
      inputs:
        - path: rtsp://192.168.1.100/stream
          roles:
            - detect
            - record
    detect:
      width: 1920
      height: 1080
      fps: 30

Correct:

yaml

cameras:
  cam1:
    ffmpeg:
      inputs:
        - path: rtsp://192.168.1.100/substream
          roles:
            - detect
        - path: rtsp://192.168.1.100/mainstream
          roles:
            - record
    detect:
      width: 1280
      height: 720
      fps: 5

Why: Using 1080p@30fps for detection wastes resources. Detection works best at 720p or lower at 5fps. Always use the camera's sub-stream for detection and main stream for recording.

错误配置：

yaml

cameras:
  cam1:
    ffmpeg:
      inputs:
        - path: rtsp://192.168.1.100/stream
          roles:
            - detect
            - record
    detect:
      width: 1920
      height: 1080
      fps: 30

正确配置：

yaml

cameras:
  cam1:
    ffmpeg:
      inputs:
        - path: rtsp://192.168.1.100/substream
          roles:
            - detect
        - path: rtsp://192.168.1.100/mainstream
          roles:
            - record
    detect:
      width: 1280
      height: 720
      fps: 5

原因： 使用1080p@30fps进行检测会浪费资源。检测在720p或更低分辨率、5帧率下效果最佳。务必使用摄像头的子流进行检测，主流进行录像。

Known Issues Prevention

已知问题预防方案

Issue	Root Cause	Solution
Bus Error	Insufficient shared memory	Set `shm-size: 256mb` in docker-compose
Database Locked	SQLite on network storage	Use `database.path: /config/frigate.db`
Green/Distorted Video	Wrong resolution in config	Match camera's actual output resolution
No Audio in Recordings	Default audio removal	Use `preset-record-generic-audio-aac`
MQTT Connection Failed	localhost in Docker	Use host IP address instead
Coral Not Detected	Missing device passthrough	Add `/dev/bus/usb` to Docker devices
High CPU Usage	Missing hwaccel	Add appropriate preset (vaapi/qsv/nvidia)
Missing Alerts	No required_zones	Configure zones with review.alerts.required_zones
UDP Stream Failures	TCP is default in Frigate	Add `preset-rtsp-udp` to input args

问题	根本原因	解决方案
总线错误	共享内存不足	在docker-compose中设置 `shm-size: 256mb`
数据库锁定	SQLite存储在网络存储	使用 `database.path: /config/frigate.db`
画面绿屏/失真	配置的分辨率错误	匹配摄像头的实际输出分辨率
录像无音频	默认移除音频	使用 `preset-record-generic-audio-aac`
MQTT连接失败	Docker内使用localhost	使用主机IP地址替代
Coral TPU未被识别	未进行设备透传	在Docker设备映射中添加 `/dev/bus/usb`
CPU占用过高	未启用硬件加速	添加对应的预设（vaapi/qsv/nvidia）
无警报触发	未配置required_zones	通过review.alerts.required_zones配置区域
UDP流失败	Frigate默认使用TCP	在输入参数中添加 `preset-rtsp-udp`

Configuration Reference

配置参考

config.yml Structure

config.yml结构

yaml

undefined

yaml

undefined

MQTT Configuration (optional but recommended)

MQTT配置（可选但推荐）

mqtt: enabled: true host: 192.168.1.50 port: 1883 user: "{FRIGATE_MQTT_USER}" password: "{FRIGATE_MQTT_PASSWORD}"

Detector Configuration

检测器配置

detectors: coral: type: edgetpu device: usb # or pci for M.2/PCIe

detectors: coral: type: edgetpu device: usb # 或pci用于M.2/PCIe接口

Global Object Settings

全局目标设置

objects: track: - person - car - dog - cat filters: person: min_area: 5000 max_area: 100000 threshold: 0.7

Recording Settings

录像设置

record: enabled: true retain: days: 1 mode: motion alerts: retain: days: 14 detections: retain: days: 7

Snapshot Settings

快照设置

snapshots: enabled: true retain: default: 7

Camera Configuration

摄像头配置

cameras: front_door: enabled: true ffmpeg: inputs: - path: "rtsp://{FRIGATE_RTSP_USER}:{FRIGATE_RTSP_PASSWORD}@192.168.1.100:554/stream1" input_args: preset-rtsp-restream roles: - detect - path: "rtsp://{FRIGATE_RTSP_USER}:{FRIGATE_RTSP_PASSWORD}@192.168.1.100:554/stream0" input_args: preset-rtsp-restream roles: - record output_args: record: preset-record-generic-audio-aac detect: width: 1280 height: 720 fps: 5 motion: mask: - 0,0,200,0,200,100,0,100 # Timestamp area zones: front_yard: coordinates: 100,500,400,500,400,720,100,720 objects: - person - car review: alerts: required_zones: - front_yard


**Key settings:**
- `detect.fps`: 5 is optimal for most cameras (reduces detector load)
- `detect.width/height`: Must match actual camera sub-stream resolution
- `record.retain.mode`: Use `motion` or `active_objects` to save storage
- `motion.mask`: Define polygons as comma-separated coordinates
- `zones.coordinates`: Bottom-center of bounding box determines zone presence

cameras: front_door: enabled: true ffmpeg: inputs: - path: "rtsp://{FRIGATE_RTSP_USER}:{FRIGATE_RTSP_PASSWORD}@192.168.1.100:554/stream1" input_args: preset-rtsp-restream roles: - detect - path: "rtsp://{FRIGATE_RTSP_USER}:{FRIGATE_RTSP_PASSWORD}@192.168.1.100:554/stream0" input_args: preset-rtsp-restream roles: - record output_args: record: preset-record-generic-audio-aac detect: width: 1280 height: 720 fps: 5 motion: mask: - 0,0,200,0,200,100,0,100 # 时间戳区域 zones: front_yard: coordinates: 100,500,400,500,400,720,100,720 objects: - person - car review: alerts: required_zones: - front_yard


**关键设置：**
- `detect.fps`：对于大多数摄像头来说，5是最优值（可降低检测器负载）
- `detect.width/height`：必须与摄像头子流的实际分辨率匹配
- `record.retain.mode`：使用`motion`或`active_objects`以节省存储空间
- `motion.mask`：用逗号分隔的坐标定义多边形
- `zones.coordinates`：目标框的底部中心位置决定其所属区域

Hardware Acceleration Presets

硬件加速预设

Intel (6th Gen+)

Intel（第6代及以上）

yaml

undefined

yaml

undefined

For Intel gen8+ (prefer QSV)

适用于Intel第8代及以上平台（优先使用QSV）

ffmpeg: hwaccel_args: preset-intel-qsv-h264 # or preset-intel-qsv-h265

ffmpeg: hwaccel_args: preset-intel-qsv-h264 # 或preset-intel-qsv-h265

For Intel gen1-gen7 (use VAAPI)

适用于Intel第1-7代平台（使用VAAPI）

ffmpeg: hwaccel_args: preset-vaapi

undefined

ffmpeg: hwaccel_args: preset-vaapi

undefined

NVIDIA GPU

yaml

ffmpeg:
  hwaccel_args: preset-nvidia

Requires NVIDIA Container Toolkit:

yaml

undefined

yaml

ffmpeg:
  hwaccel_args: preset-nvidia

需要NVIDIA容器工具包：

yaml

undefined

docker-compose.yml

services: frigate: runtime: nvidia environment: - NVIDIA_VISIBLE_DEVICES=all

undefined

services: frigate: runtime: nvidia environment: - NVIDIA_VISIBLE_DEVICES=all

undefined

AMD GPU

yaml

ffmpeg:
  hwaccel_args: preset-vaapi

yaml

ffmpeg:
  hwaccel_args: preset-vaapi

docker-compose.yml

environment:

LIBVA_DRIVER_NAME=radeonsi

undefined

environment:

LIBVA_DRIVER_NAME=radeonsi

undefined

Raspberry Pi

yaml

undefined

yaml

undefined

Raspberry Pi 4/5

ffmpeg: hwaccel_args: preset-rpi-64-h264 # or preset-rpi-64-h265


Requires: `gpu_mem=128` in `/boot/config.txt` and device mapping in Docker.

ffmpeg: hwaccel_args: preset-rpi-64-h264 # 或preset-rpi-64-h265


要求：在`/boot/config.txt`中设置`gpu_mem=128`，并在Docker中进行设备映射。

Object Detector Types

目标检测器类型

USB Coral TPU

yaml

detectors:
  coral:
    type: edgetpu
    device: usb  # Single USB Coral
    # device: usb:0  # First of multiple USB Corals

Docker device mapping:

yaml

devices:
  - /dev/bus/usb:/dev/bus/usb

yaml

detectors:
  coral:
    type: edgetpu
    device: usb  # 单个USB Coral
    # device: usb:0  # 多个USB Coral中的第一个

Docker设备映射：

yaml

devices:
  - /dev/bus/usb:/dev/bus/usb

M.2/PCIe Coral TPU

yaml

detectors:
  coral:
    type: edgetpu
    device: pci
    # device: pci:0  # First of multiple PCIe Corals

yaml

detectors:
  coral:
    type: edgetpu
    device: pci
    # device: pci:0  # 多个PCIe Coral中的第一个

OpenVINO (Intel)

OpenVINO（Intel）

yaml

detectors:
  ov:
    type: openvino
    device: GPU  # or CPU

model:
  path: /openvino-model/ssdlite_mobilenet_v2.xml
  width: 300
  height: 300

yaml

detectors:
  ov:
    type: openvino
    device: GPU  # 或CPU

model:
  path: /openvino-model/ssdlite_mobilenet_v2.xml
  width: 300
  height: 300

ONNX (Multi-GPU)

ONNX（多GPU）

yaml

detectors:
  onnx:
    type: onnx
    # Automatically uses: ROCm (AMD), OpenVINO (Intel), TensorRT (NVIDIA)

yaml

detectors:
  onnx:
    type: onnx
    # 自动适配：ROCm（AMD）、OpenVINO（Intel）、TensorRT（NVIDIA）

Advanced Features

高级功能

Zone-Based Speed Estimation

基于区域的速度估算

yaml

zones:
  driveway:
    coordinates: 100,500,400,500,400,720,100,720
    distances:
      - "100,500|400,500|20ft"  # 20 feet between points
    speed:
      threshold: 15  # Minimum mph to register

yaml

zones:
  driveway:
    coordinates: 100,500,400,500,400,720,100,720
    distances:
      - "100,500|400,500|20ft"  # 两点间距离为20英尺
    speed:
      threshold: 15  # 触发速度的最低阈值（英里/小时）

Audio Detection

音频检测

yaml

audio:
  enabled: true
  listen:
    - bark
    - fire_alarm
    - scream
    - speech

cameras:
  front_door:
    ffmpeg:
      inputs:
        - path: rtsp://camera/stream
          roles:
            - audio

yaml

audio:
  enabled: true
  listen:
    - bark
    - fire_alarm
    - scream
    - speech

cameras:
  front_door:
    ffmpeg:
      inputs:
        - path: rtsp://camera/stream
          roles:
            - audio

GenAI Event Descriptions

生成式AI事件描述

yaml

genai:
  enabled: true
  provider: ollama
  base_url: http://192.168.1.100:11434
  model: llava

yaml

genai:
  enabled: true
  provider: ollama
  base_url: http://192.168.1.100:11434
  model: llava

Face Recognition (Frigate+)

人脸识别（Frigate+）

yaml

face_recognition:
  enabled: true
  threshold: 0.6

cameras:
  front_door:
    detect:
      width: 1280  # Higher res improves face detection

yaml

face_recognition:
  enabled: true
  threshold: 0.6

cameras:
  front_door:
    detect:
      width: 1280  # 更高分辨率可提升人脸识别效果

License Plate Recognition

车牌识别

yaml

lpr:
  enabled: true

cameras:
  driveway:
    lpr:
      enabled: true

yaml

lpr:
  enabled: true

cameras:
  driveway:
    lpr:
      enabled: true

go2rtc Integration

go2rtc集成

yaml

go2rtc:
  streams:
    front_door:
      - rtsp://user:pass@192.168.1.100:554/stream1
      - "ffmpeg:front_door#video=copy#audio=opus"
  webrtc:
    candidates:
      - 192.168.1.50:8555
      - stun:8555

yaml

go2rtc:
  streams:
    front_door:
      - rtsp://user:pass@192.168.1.100:554/stream1
      - "ffmpeg:front_door#video=copy#audio=opus"
  webrtc:
    candidates:
      - 192.168.1.50:8555
      - stun:8555

Docker Compose Template

Docker Compose模板

yaml

services:
  frigate:
    container_name: frigate
    image: ghcr.io/blakeblackshear/frigate:stable
    restart: unless-stopped
    shm_size: "256mb"
    devices:
      - /dev/bus/usb:/dev/bus/usb  # USB Coral
      - /dev/dri/renderD128:/dev/dri/renderD128  # Intel GPU
    volumes:
      - ./config:/config
      - ./storage:/media/frigate
      - type: tmpfs
        target: /tmp/cache
        tmpfs:
          size: 1000000000
    ports:
      - "8971:8971"  # Web UI
      - "8554:8554"  # RTSP feeds
      - "8555:8555/tcp"  # WebRTC
      - "8555:8555/udp"  # WebRTC
    environment:
      FRIGATE_RTSP_USER: admin
      FRIGATE_RTSP_PASSWORD: ${RTSP_PASSWORD}
      FRIGATE_MQTT_USER: frigate
      FRIGATE_MQTT_PASSWORD: ${MQTT_PASSWORD}

yaml

services:
  frigate:
    container_name: frigate
    image: ghcr.io/blakeblackshear/frigate:stable
    restart: unless-stopped
    shm_size: "256mb"
    devices:
      - /dev/bus/usb:/dev/bus/usb  # USB Coral
      - /dev/dri/renderD128:/dev/dri/renderD128  # Intel GPU
    volumes:
      - ./config:/config
      - ./storage:/media/frigate
      - type: tmpfs
        target: /tmp/cache
        tmpfs:
          size: 1000000000
    ports:
      - "8971:8971"  # Web UI
      - "8554:8554"  # RTSP流
      - "8555:8555/tcp"  # WebRTC
      - "8555:8555/udp"  # WebRTC
    environment:
      FRIGATE_RTSP_USER: admin
      FRIGATE_RTSP_PASSWORD: ${RTSP_PASSWORD}
      FRIGATE_MQTT_USER: frigate
      FRIGATE_MQTT_PASSWORD: ${MQTT_PASSWORD}

Bundled Resources

附带资源

Templates

模板

Located in

templates/

```
docker-compose.yml
```
- Production-ready compose file
```
config-minimal.yml
```
- Minimal starter config
```
config-full.yml
```
- Full-featured config template

位于

templates/

目录下：

```
docker-compose.yml
```
- 生产环境可用的Compose文件
```
config-minimal.yml
```
- 最简入门配置
```
config-full.yml
```
- 全功能配置模板

References

参考文档

Located in

references/

```
detector-comparison.md
```
- Detector performance comparison
```
ffmpeg-presets.md
```
- All available FFmpeg presets
```
mqtt-topics.md
```
- MQTT topic reference

位于

references/

目录下：

```
detector-comparison.md
```
- 检测器性能对比
```
ffmpeg-presets.md
```
- 所有可用的FFmpeg预设
```
mqtt-topics.md
```
- MQTT主题参考

Scripts

脚本

Located in

scripts/

```
validate-config.sh
```
- Validate config syntax before applying

位于

scripts/

目录下：

```
validate-config.sh
```
- 在应用前验证配置语法

Dependencies

依赖项

Required

必需依赖

Package	Version	Purpose
Docker	20.10+	Container runtime
docker-compose	2.0+	Service orchestration

软件包	版本	用途
Docker	20.10+	容器运行时
docker-compose	2.0+	服务编排

Optional

可选依赖

Package	Version	Purpose
NVIDIA Container Toolkit	Latest	NVIDIA GPU support
Coral Edge TPU runtime	Latest	Coral TPU support

软件包	版本	用途
NVIDIA容器工具包	最新版	NVIDIA GPU支持
Coral Edge TPU运行时	最新版	Coral TPU支持

Official Documentation

官方文档

Troubleshooting

故障排查

Camera Shows Offline

摄像头显示离线

Symptoms: Camera fps shows 0, web UI shows offline status

Solution:

bash

undefined

症状： 摄像头帧率显示为0，Web UI显示离线状态

解决方案：

bash

undefined

Test RTSP URL directly

直接测试RTSP URL

ffprobe -rtsp_transport tcp "rtsp://user:pass@ip:554/stream"

Check Docker logs

查看Docker日志

docker logs frigate 2>&1 | grep -i "camera_name"

undefined

docker logs frigate 2>&1 | grep -i "camera_name"

undefined

High CPU Usage

CPU占用过高

Symptoms: CPU consistently above 80%, system becomes unresponsive

Solution:

Enable hardware acceleration (see presets above)
Reduce detect fps from 10 to 5
Lower detect resolution to 720p or below
Add Coral TPU for object detection

症状： CPU持续高于80%，系统无响应

解决方案：

启用硬件加速（参考上方预设）
将检测帧率从10降低到5
将检测分辨率降至720p或更低
添加Coral TPU进行目标检测

No Objects Detected

无目标被检测到

Symptoms: Motion detected but no object events created

Solution:

Verify detector is configured and running: check
```
/api/stats
```
Check object filters aren't too restrictive (min_area, threshold)
Ensure detect stream resolution is correct
Verify objects list includes desired types

症状： 检测到运动但未生成目标事件

解决方案：

验证检测器已配置并运行：查看
```
/api/stats
```
检查目标过滤器是否过于严格（min_area、threshold）
确保检测流分辨率正确
验证目标列表包含所需类型

Recording Not Working

录像功能不工作

Symptoms: Events show but no recordings available

Solution:

yaml

undefined

症状： 显示事件但无可用录像

解决方案：

yaml

undefined

Ensure record role is assigned

确保已分配record角色

cameras: cam1: ffmpeg: inputs: - path: rtsp://camera/stream roles: - record # Must be explicitly set record: enabled: true # Must be true

undefined

cameras: cam1: ffmpeg: inputs: - path: rtsp://camera/stream roles: - record # 必须显式设置 record: enabled: true # 必须设置为true

undefined